CellWhisperer bridges the gap between transcriptomics data and natural language, enabling intuitive interaction with scRNA-seq datasets.
(Click the annotated screenshot for a 2-minute video-tutorial)
CellWhisperer constitutes a proof-of-concept for interactive exploration of scRNA-seq data. Like other AI models, CellWhisperer does not understand user questions in a human sense, and it can make mistakes. Key results should thus be reconfirmed with conventional bioinformatics approaches.
The CellWhisperer server linked above provides example datasets but does not allow for upload of user-provided datasets. To analyze your own data with CellWhisperer, you need to run CellWhisperer on your computer or on a local server. This is relatively straightforward to set up in three steps:
A step-by-step description is provided in the CellWhisperer GitHub repository.
If you use CellWhisperer in your research, please cite us:
Moritz Schaefer*, Peter Peneder*, Daniel Malzl, Salvo Danilo Lombardo, Mihaela Peycheva, Jake Burton, Anna Hakobyan, Varun Sharma, Thomas Krausgruber, Celine Sin, Jörg Menche, Eleni M. Tomazou, Christoph Bock (2025) Multimodal learning enables chat-based exploration of single-cell data. Nature Biotechnology (in press). DOI: 10.1038/s41587-025-02857-9
* equal contribution
Preprint: bioRxiv
Got feedback? Drop us an email at cellwhisperer@bocklab.org or open an issue on GitHub.